How to Accelerate Efficiency with Virtual Twins and AI in Manufacturing

We constantly hear from manufacturing leaders about the challenges of staying competitive and navigating the world of new innovation and technology. Some of the most vocal comments come from high-tech industries, where product lifecycles are shrinking, complexity is increasing, and their skilled workers are becoming harder to retain.    

In the previous Dassault Systèmes and Arch Systems joint blog post and webinar, we explored the transformative potential of virtual twins in addressing these manufacturing challenges. We also discussed how these dynamic, real-time models can integrate data from across the manufacturing ecosystem to drive efficiency, reduce downtime, and optimize resource utilization.    

In this blog post, we take a deeper dive into how artificial intelligence (AI) is accelerating the power of virtual twins, enabling manufacturers to achieve new levels of productivity and quality. We’ll also discuss the importance of a unified namespace in connecting data and knowledge and share some real-world success stories from our customers.

The Power of Virtual Twins and AI in Manufacturing

Leading manufacturers are already using AI as a critical addition to virtual twin technology. By applying machine learning and other AI techniques to the vast amounts of data generated by modern factories, they are unlocking insights and automating actions that enable them to stay ahead of their competition. Here are a few examples:

• Predictive Maintenance: AI in manufacturing can analyze sensor data and machine logs to predict when equipment is likely to fail, allowing manufacturers to proactively schedule maintenance and avoid costly downtime.    
• Quality Control: AI identifies patterns and anomalies in production data to pinpoint root causes of quality issues. This enables faster resolution and continuous improvement.    
• Root Cause Analysis: By correlating data from various sources, AI in manufacturing can help manufacturers quickly identify the underlying causes of production problems, whether they stem from machines, materials, or processes.  
• Process Optimization: Artificial intelligence can analyze production data to identify bottlenecks and inefficiencies in manufacturing processes. This allows manufacturers to optimize workflows, improve resource allocation, and reduce waste.
• Yield Improvement: By identifying patterns and correlations in production data, AI can help manufacturers pinpoint factors that contribute to yield loss and implement corrective actions to improve overall yield.
• Supply Chain Resilience: AI in manufacturing can simulate disruptions and predict potential bottlenecks in the supply chain, allowing manufacturers to proactively mitigate risks and ensure business continuity.

The Unified Namespace: Connecting Data and Knowledge

To fully realize the benefits of AI and virtual twins, manufacturers must first integrate data from a variety of operational sources. This includes machines, sensors, and even the tacit knowledge of experienced workers. This is where the concept of a unified namespace comes in.

A unified namespace provides a single, consistent reference point for all data across manufacturing operations. This “single source of truth” enables seamless data integration and AI algorithms to access and analyze information from disparate sources. But capturing information from machines and systems is not the only piece of the puzzle. The unified namespace must also integrate and preserve the critical knowledge of experienced workers, ensuring that this expertise is not lost as the workforce evolves.

Real-World Success Stories

There are multiple proof points for success across high-tech and many different industries. Next, we’ll each highlight a success story from our customers. These companies are already seeing benefits from the combination of virtual twins and artificial intelligence. These examples demonstrate the tangible manufacturing benefits and return on investment (ROI) that these technologies can deliver:

• Proactive Quality Management
  • Historically, manufacturers have often relied on their expertise and intuition to identify and address potential quality issues. However, with the implementation of a virtual twin, they are now able to proactively analyze processes and anticipate potential problems. The virtual twin enabled the creation and maintenance of PFMEA (Process Failure Mode and Effects Analysis) and control plans. This provides a structured approach to quality management and reducing the risk of defects and production delays.
• Accelerated Quality Insights
  • Engineering teams previously spent countless hours manually analyzing data from hundreds or even thousands of sensors to identify quality issues. By integrating AI with the virtual twin, they are able to significantly speed up the process of gaining quality insights. The AI-powered system could automatically analyze vast amounts of data and identify patterns and anomalies. It could pinpoint the root causes of defects, allowing the engineer to focus on implementing solutions and improving overall quality. 
• Electronics Manufacturer Prevents Component Attrition
  • A global electronics manufacturer faced challenges with component attrition from 15,000 feeders across their factories.  Artificial intelligence to analyze attrition data for anomalies and identify problematic feeders.  By tracking serial numbers and removing or repairing these feeders, they achieved a 33% reduction in global attrition.  This translated to over $5 million in savings, compared to a few $100,000 for hardware and maintenance in part replacements.    

These are just a few examples of the numerous applications and significant benefits of virtual twin and artificial intelligence technology. Together they drive manufacturing efficiency to realize a tangible value.

Conclusion

The virtual twins value, accelerated by AI applications in manufacturing, is key to the next challenges faced by manufacturing leaders. These innovative technologies offer unprecedented capabilities for optimization, efficiency, and continuous improvement. By embracing these technologies, manufacturers can leapfrog their competition, while laying the foundation for an agile, resilient, and innovative future.

Ready to unlock the full potential of your manufacturing operations with virtual twins and AI? Visit our websites Dassault Systèmes and Arch Systems. Contact us today to learn more about how our joint solutions can help you achieve your business goals.